The popularity of wireless communication accelerates research on new technologies that are required to satisfy users' needs. Wireless mesh networks (WMNs), which are additional access technologies instead of being a renewed one, have an important place among next-generation wireless networks. In particular, the capability of working without any infrastructure is the most outstanding advantage of WMNs. There are many studies aimed at WMNs, particularly channel assignment and routing methods for multichannel multiradio structures that provide higher data capacity. Interference, which has a direct effect on the quality of communication, is still a challenge to be addressed. In this study, multichannel multiradio WMNs and various channel assignment schemes are analyzed. Directional mesh (DMesh) architecture, which uses directional antennas to form a multichannel structure, is analyzed in terms of channel assignment procedure. A new interference-aware channel assignment scheme that aims to eliminate DMesh's disadvantages is proposed and performances of both schemes are compared. Several results of experimental analysis prove that the proposed channel assignment scheme improves the performance of DMesh.
Cloud computing that aims to provide convenient, on-demand, network access to shared software and hardware resources has security as the greatest challenge. Data security is the main security concern followed by intrusion detection and prevention in cloud infrastructure. In this chapter, general information about cloud computing and its security issues are discussed. In order to prevent or avoid many attacks, a number of machine learning algorithms approaches are proposed. However, these approaches do not provide efficient results for identifying unknown types of attacks. Deep learning enables to learning features that are more complex, and thanks to the collection of big data as a training data, deep learning achieves more successful results. Many deep learning algorithms are proposed for attack detection. Deep networks architecture is divided into two categories, and descriptions for each architecture and its related attack detection studies are discussed in the following section of chapter.
Cloud computing that aims to provide convenient, on-demand, network access to shared software and hardware resources has security as the greatest challenge. Data security is the main security concern followed by intrusion detection and prevention in cloud infrastructure. In this chapter, general information about cloud computing and its security issues are discussed. In order to prevent or avoid many attacks, a number of machine learning algorithms approaches are proposed. However, these approaches do not provide efficient results for identifying unknown types of attacks. Deep learning enables to learning features that are more complex, and thanks to the collection of big data as a training data, deep learning achieves more successful results. Many deep learning algorithms are proposed for attack detection. Deep networks architecture is divided into two categories, and descriptions for each architecture and its related attack detection studies are discussed in the following section of chapter.
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